Increasing the accountability of automated decision-making systems: An assessment of the automated decision-making system introduced in Canada's temporary resident visa immigration stream

Abstract

States are increasingly turning to automated decision-making systems to increase efficiency in program and service delivery. While automation offers several desirable benefits, great care must be given to establishing and increasing the accountability of automated decision-making systems in the public sector. This paper focuses on accountability in automated decision-making systems in migration management. A key issue is what the impact of automated decision-making is on accountability in migration management? This paper seeks to explore this question by evaluating the accountability mechanisms established by the Canadian government in the use of automated decision-making systems to triage Temporary Resident Visa immigration applications. This paper begins with an explanation of the interaction between public administration and digital governance, with a particular focus on the human decision-making component of public administration and a review of accountability in the public sector. What follows is an explanation of how decision-making in Canada's Temporary Resident Visa Application stream traditionally occurs. A brief review of the Canadian Algorithmic Impact Assessment Tool introduces a thorough explanation of the Canadian government's Temporary Resident Visa (TRV) eApps Advanced Analytics Pilot to showcase changes between the traditional human decision-making process and the more recent experiment engaging automated decision-making in this particular immigration stream. The paper concludes by posing a question on what accountability amounts to for the Canadian government and whether the accountability measures introduced in Canada's TRV Pilot are sufficient.